Triple
T5531596
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Damage (1992 film) |
E145060
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
LWT
LWT (London Weekend Television) was a major British television company and ITV franchise holder known for producing a wide range of popular entertainment and drama programming.
|
E529056
|
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: LWT | Statement: [Damage (1992 film), productionCompany, LWT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LWT Context triple: [Damage (1992 film), productionCompany, LWT]
-
A.
Saftleven
Saftleven is a Dutch family name most notably associated with a 17th-century artistic dynasty of painters and draughtsmen from the Netherlands.
-
B.
Labná
Labná is a small ancient Maya archaeological site in Mexico’s Yucatán Peninsula, noted for its ornate Puuc-style architecture and iconic arched gateway.
-
C.
Manteigas
Manteigas is a small mountain town in central Portugal, known for its scenic location in the Serra da Estrela range and its natural landscapes.
-
D.
WOK
WOK is the National Rail station code for Woking railway station in Surrey, England.
-
E.
L&M
L&M is an international cigarette brand owned by Philip Morris, known for its mid-priced positioning in the global tobacco market.
- 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: LWT Triple: [Damage (1992 film), productionCompany, LWT]
Generated description
LWT (London Weekend Television) was a major British television company and ITV franchise holder known for producing a wide range of popular entertainment and drama programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LWT Target entity description: LWT (London Weekend Television) was a major British television company and ITV franchise holder known for producing a wide range of popular entertainment and drama programming.
-
A.
Saftleven
Saftleven is a Dutch family name most notably associated with a 17th-century artistic dynasty of painters and draughtsmen from the Netherlands.
-
B.
Labná
Labná is a small ancient Maya archaeological site in Mexico’s Yucatán Peninsula, noted for its ornate Puuc-style architecture and iconic arched gateway.
-
C.
Manteigas
Manteigas is a small mountain town in central Portugal, known for its scenic location in the Serra da Estrela range and its natural landscapes.
-
D.
WOK
WOK is the National Rail station code for Woking railway station in Surrey, England.
-
E.
L&M
L&M is an international cigarette brand owned by Philip Morris, known for its mid-priced positioning in the global tobacco market.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f9d17ec8190b93b12931a4c1b33 |
completed | March 22, 2026, 4:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c02805a174819096cd16f2c1ef2eb1 |
completed | March 22, 2026, 5:33 p.m. |
| NEDg | Description generation | batch_69c033ddc7148190ba64ebfc2472c367 |
completed | March 22, 2026, 6:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c036725fc481908ab0e260892d8243 |
completed | March 22, 2026, 6:35 p.m. |
Created at: March 22, 2026, 3:34 p.m.