Triple
T13934258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zohra Lampert |
E335073
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Pay or Die!
Pay or Die! is a 1960 crime drama film about the real-life efforts of New York police officer Joseph Petrosino to combat the Black Hand extortion racket in the Italian-American community.
|
E1070337
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Pay or Die! | Statement: [Zohra Lampert, notableWork, Pay or Die!]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pay or Die! Context triple: [Zohra Lampert, notableWork, Pay or Die!]
-
A.
Payback
Payback is a 1999 neo-noir crime film starring Mel Gibson as a vengeful thief seeking repayment after being double-crossed.
-
B.
Win, Lose or Die
"Win, Lose or Die" is a James Bond novel by British author John Gardner that follows 007 as he tackles a high-stakes terrorist plot involving NATO and global security.
-
C.
Pay to Play
"Pay to Play" is a song by American punk rock band Lenny.
-
D.
Don’t Pay 4 It
Don’t Pay 4 It is a track featured on the hip-hop album "Kiss the Ring" by DJ Khaled.
-
E.
Do or Die
"Do or Die" is the historic call to action issued by Mahatma Gandhi during the Quit India Movement of 1942, urging Indians to fight for complete independence from British rule with unwavering resolve.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pay or Die! Triple: [Zohra Lampert, notableWork, Pay or Die!]
Generated description
Pay or Die! is a 1960 crime drama film about the real-life efforts of New York police officer Joseph Petrosino to combat the Black Hand extortion racket in the Italian-American community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pay or Die! Target entity description: Pay or Die! is a 1960 crime drama film about the real-life efforts of New York police officer Joseph Petrosino to combat the Black Hand extortion racket in the Italian-American community.
-
A.
Payback
Payback is a 1999 neo-noir crime film starring Mel Gibson as a vengeful thief seeking repayment after being double-crossed.
-
B.
Win, Lose or Die
"Win, Lose or Die" is a James Bond novel by British author John Gardner that follows 007 as he tackles a high-stakes terrorist plot involving NATO and global security.
-
C.
Pay to Play
"Pay to Play" is a song by American punk rock band Lenny.
-
D.
Don’t Pay 4 It
Don’t Pay 4 It is a track featured on the hip-hop album "Kiss the Ring" by DJ Khaled.
-
E.
Do or Die
"Do or Die" is the historic call to action issued by Mahatma Gandhi during the Quit India Movement of 1942, urging Indians to fight for complete independence from British rule with unwavering resolve.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf28df081908d897d7b9ec7939d |
completed | April 14, 2026, 12:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce865ab4819088221189344b3801 |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f9fd5d4abc8190aa10d9f1c9f7f9c9 |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fb14bfa2c081908381bb74f040c6c8 |
completed | May 6, 2026, 10:15 a.m. |
Created at: April 9, 2026, 10:17 p.m.