Triple
T14392611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marty Brennaman |
E356881
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Marty |
E789312
|
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: Marty | Statement: [Marty Brennaman, givenName, Marty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marty Context triple: [Marty Brennaman, givenName, Marty]
-
A.
Marty
Marty is a 1955 American romantic drama film that won the Academy Award for Best Picture and is renowned for its poignant portrayal of a lonely butcher’s search for love.
-
B.
Marty
chosen
Marty is a common diminutive form of the given name Martin, often used as a familiar or informal nickname.
-
C.
Marty
Marty is a common diminutive form of the given name Martha.
-
D.
Marty
Marty is a surname of French origin, notably borne by figures such as André Marty, a prominent French communist and political activist.
-
E.
Marty
Marty is a central character in the 1996 ensemble drama film "Beautiful Girls," known for her youthful charm and pivotal role in the story’s exploration of love and growing up.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de902b9acc8190817ffa848a76a880 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5517f5e481908fd65177c34f4282 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:16 a.m.