Triple
T839828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phillip A. Sharp |
E18151
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Phillip |
E87545
|
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: Phillip | Statement: [Phillip A. Sharp, givenName, Phillip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phillip Context triple: [Phillip A. Sharp, givenName, Phillip]
-
A.
Phillip
chosen
Phillip is the given first name of former NFL quarterback and sports broadcaster Phil Simms.
-
B.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
C.
Philip
Philip is the given first name of Phil Esposito, the Hall of Fame Canadian ice hockey center and former NHL star.
-
D.
Philip
Philip was the given name of Philip V, the first Bourbon king of Spain who reigned in the early 18th century.
-
E.
Philip
Philip is one of the Twelve Apostles of Jesus in Christian tradition, recognized as an early follower and messenger of Christ.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe4ab1081909207ae2eec1898d9 |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6efcc37c81908fd49ad65818eb0c |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:38 p.m.