Triple
T1210574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Franks |
E25989
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tommy |
E67600
|
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: Tommy | Statement: [Tommy Franks, givenName, Tommy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tommy Context triple: [Tommy Franks, givenName, Tommy]
-
A.
Tommy
chosen
Tommy is a masculine given name, often a diminutive of Thomas, used in various English-speaking countries.
-
B.
Tommy Hawk
Tommy Hawk is the anthropomorphic hawk mascot of the NHL’s Chicago Blackhawks, known for entertaining fans with energetic antics at games and community events.
-
C.
Tommy Gunn
Tommy Gunn is a fictional heavyweight boxer who becomes Rocky Balboa’s protégé-turned-rival in the film "Rocky V."
-
D.
Tom
Tom is a common masculine given name, often used in English-speaking countries as a short form of Thomas.
-
E.
Tommy Ross
Tommy Ross is a popular high school student in Stephen King’s horror novel "Carrie," known for his pivotal role in inviting Carrie White to the prom.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bde4670481908c16a3a8c1a54aad |
completed | March 1, 2026, 10:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8a0b1ad8819098a89585fe6ba090 |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:46 p.m.