Triple
T6299949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Wood |
E141227
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wood |
E109794
|
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: Wood | Statement: [Andrew Wood, familyName, Wood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wood Context triple: [Andrew Wood, familyName, Wood]
-
A.
Wood
chosen
Wood is a common English surname with historical roots in Britain, often originally referring to someone who lived or worked near a forest.
-
B.
Wooden
Wooden is a surname most famously associated with John Wooden, the legendary American college basketball coach known for his success at UCLA.
-
C.
Lenswood
Lenswood is a small rural town in South Australia's Adelaide Hills region, known for its cool-climate orchards and scenic vineyards.
-
D.
Oak
Oak is the professional name of Warren “Oak” Felder, a Grammy-nominated songwriter and record producer known for his work with major contemporary pop and R&B artists.
-
E.
Maderas
Maderas is a stratovolcano on Ometepe Island in Lake Nicaragua, known for its cloud forest, crater lagoon, and popular hiking trails.
- 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0645a7e048190af7a609fc74b876a |
completed | March 22, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e427de4481909f1cad8fae93bc42 |
completed | March 27, 2026, 1:58 a.m. |
Created at: March 22, 2026, 4:27 p.m.