Triple
T15497982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lesley Sharp |
E378870
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Woods |
E776463
|
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: The Woods | Statement: [Lesley Sharp, notableWork, The Woods]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Woods Context triple: [Lesley Sharp, notableWork, The Woods]
-
A.
The Woods
chosen
The Woods is a film scored by composer John Frizzell, known for its atmospheric and suspenseful musical style.
-
B.
The Woods
The Woods is a residential neighborhood within the planned community of Burke Centre in Fairfax County, Virginia.
-
C.
The Woods
"The Woods" is a soulful, genre-blending song by American musician Raury that showcases his introspective lyrics and folk-influenced alternative sound.
-
D.
In the Woods
In the Woods is a 19th-century landscape painting by American artist Asher B. Durand, exemplifying the Hudson River School’s detailed and reverent depiction of the natural world.
-
E.
The Wood
"The Wood" is a 1999 coming-of-age comedy-drama film that follows three lifelong friends in Inglewood, California, as they reminisce about their youth on the day of one friend's wedding.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fb0aee081909db1c54349ec8492 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3667a53c81908be789f99e580265 |
completed | May 9, 2026, 1:28 p.m. |
Created at: April 10, 2026, 3:53 a.m.