Triple
T22958627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolf Tobin |
E570828
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Tobin |
—
|
NE NERFINISHED |
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: Tobin | Statement: [Wolf Tobin, familyName, Tobin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tobin Context triple: [Wolf Tobin, familyName, Tobin]
-
A.
Tobin
chosen
Tobin is the given name of Tobin Heath, an American professional soccer player and multiple-time FIFA Women's World Cup champion.
-
B.
Bullard
Bullard is an English surname borne by various notable figures, including diplomats, politicians, and artists.
-
C.
Thaler
The Thaler was a large silver coin and monetary unit widely used across various German states and parts of Europe from the 16th to 19th centuries, serving as a precursor to the modern dollar.
-
D.
Fama
Fama is the surname of Eugene Fama, a Nobel Prize–winning American economist renowned for his work on efficient markets and asset pricing.
-
E.
Donald Markowitz
Donald Markowitz is a songwriter best known for co-writing the Academy Award–winning hit "(I've Had) The Time of My Life" from the film Dirty Dancing.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f2ce9c8190977f146771816341 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.