Triple
T4039397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen |
E83906
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Steve |
E115529
|
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: Steve | Statement: [Stephen, hasDiminutive, Steve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Context triple: [Stephen, hasDiminutive, Steve]
-
A.
Steven
Steven is the given first name of American film producer and New York Giants co-owner Steve Tisch.
-
B.
Steven
chosen
Steven is a masculine given name of English origin, often used as a variant of Stephen.
-
C.
Steven
Steven is the given first name of Steve Albini, the influential American musician, recording engineer, and producer known for his work with numerous alternative rock bands.
-
D.
Steven
Steven is the given first name of former Major League Baseball first baseman and ten-time All-Star Steve Garvey.
-
E.
Steven
Steven is the birth name of Steve Jobs, the influential co-founder and longtime leader of Apple Inc.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb37e24c81908d6357ab8ba5388d |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56299dbe88190b36f4a488201acd8 |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 9, 2026, 3:37 p.m.