Triple
T7822768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nat Hickey |
E181170
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Nat |
E409212
|
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: Nat | Statement: [Nat Hickey, givenName, Nat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nat Context triple: [Nat Hickey, givenName, Nat]
-
A.
Nat
chosen
Nat is a fictional character from Louisa May Alcott's novel "Jo's Boys," known as one of the former students of Plumfield whose adult life and growth are followed in the story.
-
B.
Na
Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
-
C.
Nu
Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
-
D.
Natata
Natata is a small settlement located on Butaritari Atoll in the Pacific island nation of Kiribati.
-
E.
Nal
Nal is an entity or individual that serves as a point of comparison to Amri, suggesting they share similar characteristics, roles, or contexts.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cafa095d7081908b3e492ce58b5d5f |
completed | March 30, 2026, 10:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14a526cc8190a8b1a3179f75ad6c |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 4:41 p.m.