Triple
T9347490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan Sims |
E224927
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Sykes |
E749450
|
NE FINISHED |
How this triple was built (2 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: Sykes | Statement: [Joan Sims, notableWork, Sykes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sykes Context triple: [Joan Sims, notableWork, Sykes]
-
A.
Sykes
chosen
Sykes is a British television sitcom best known for starring comedian Eric Sykes in a series of domestic and comedic misadventures.
-
B.
Sykes
Sykes is an English surname of Old Norse origin, commonly associated with families from northern England.
-
C.
Moneague
Moneague is a rural village in Jamaica known for its karst landscape, seasonal lake, and location along the main road through Saint Ann Parish.
-
D.
Mosby
Mosby is a surname most famously associated with John S. Mosby, a Confederate cavalry battalion commander and guerrilla leader during the American Civil War.
-
E.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca842993248190a79ab06968994b86 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f0f4c4c8190a94c0d44ef349d7d |
completed | April 1, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e432106c81908ae080f37bc80f3f |
completed | April 4, 2026, 10:13 a.m. |
Created at: March 30, 2026, 7:41 p.m.