Triple
T15138364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lydney Park |
E361615
|
entity |
| Predicate | excavatedBy |
P7650
|
FINISHED |
| Object | Tessa Wheeler |
E738218
|
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: Tessa Wheeler | Statement: [Lydney Park, excavatedBy, Tessa Wheeler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Wheeler Context triple: [Lydney Park, excavatedBy, Tessa Wheeler]
-
A.
Tessa Wheeler
chosen
Tessa Wheeler was a pioneering early 20th-century British archaeologist known for her influential excavations and contributions to developing modern archaeological methods.
-
B.
Tessa Ross
Tessa Ross is a prominent British film and television producer known for backing acclaimed, often auteur-driven projects across UK cinema and high-end TV drama.
-
C.
Tessa Wall
Tessa Wall is the mother of Fats Wall, a character in J.K. Rowling’s novel "The Casual Vacancy."
-
D.
Tessa Piggott
Tessa Piggott is the central protagonist of the British television drama series "Love Hurts," around whose personal and professional life the story revolves.
-
E.
Tamsin Carroll
Tamsin Carroll is an Australian actress and singer best known for her work in musical theatre in both Australia and the United Kingdom.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b59b488190b0016970647e7483 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d92c9788190aa4523a1e47bc561 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 3:07 a.m.