Triple
T10633718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebekah Staton |
E250523
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Pulling
Pulling is a British television comedy series known for its darkly humorous portrayal of three single women navigating chaotic relationships and adulthood.
|
E876417
|
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: Pulling | Statement: [Rebekah Staton, notableWork, Pulling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pulling Context triple: [Rebekah Staton, notableWork, Pulling]
-
A.
Puller
Puller is a surname most prominently associated with the decorated U.S. Marine Corps officer Lewis B. "Chesty" Puller and his family.
-
B.
Traction
Traction is the common nickname for the Citroën Traction Avant, a pioneering French automobile famous for its early use of front-wheel drive and unitary body construction.
-
C.
Drag
Drag is a small coastal village in Nordland county, Norway, known for its scenic fjord-side location and proximity to the Tysfjord.
-
D.
Drag
Drag is a 1997 studio album by k.d. lang featuring smoky, lounge-influenced covers themed around addiction and dependency.
-
E.
Pulleine
Pulleine is an English surname historically associated with British military and public figures.
- 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: Pulling Triple: [Rebekah Staton, notableWork, Pulling]
Generated description
Pulling is a British television comedy series known for its darkly humorous portrayal of three single women navigating chaotic relationships and adulthood.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pulling Target entity description: Pulling is a British television comedy series known for its darkly humorous portrayal of three single women navigating chaotic relationships and adulthood.
-
A.
Puller
Puller is a surname most prominently associated with the decorated U.S. Marine Corps officer Lewis B. "Chesty" Puller and his family.
-
B.
Traction
Traction is the common nickname for the Citroën Traction Avant, a pioneering French automobile famous for its early use of front-wheel drive and unitary body construction.
-
C.
Drag
Drag is a small coastal village in Nordland county, Norway, known for its scenic fjord-side location and proximity to the Tysfjord.
-
D.
Drag
Drag is a 1997 studio album by k.d. lang featuring smoky, lounge-influenced covers themed around addiction and dependency.
-
E.
Pulleine
Pulleine is an English surname historically associated with British military and public figures.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfab47bc819086684edc1b6dce74 |
completed | April 8, 2026, 11:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96bbd64d8819089d55af875d39e45 |
completed | April 10, 2026, 9:29 p.m. |
| NEDg | Description generation | batch_69d9701de92881908c0b8f05eae97e35 |
completed | April 10, 2026, 9:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d970f3f78081909bcb2dae6dae06d5 |
completed | April 10, 2026, 9:51 p.m. |
Created at: April 8, 2026, 9:02 p.m.