Triple
T19289357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sterna Segal |
E482398
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Segal |
—
|
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: Segal | Statement: [Sterna Segal, familyName, Segal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Segal Context triple: [Sterna Segal, familyName, Segal]
-
A.
Segal
chosen
Segal is a common Ashkenazi Jewish surname of Hebrew origin, traditionally associated with priestly (Levite) lineage.
-
B.
Segall
Segall is a surname most notably associated with American garage rock and psychedelic musician Ty Segall.
-
C.
Seulberg
Seulberg is a district of the town of Friedrichsdorf in the Hochtaunus region of Hesse, Germany.
-
D.
Sergel
Sergel is a Swedish surname most notably associated with the 18th-century sculptor Johan Tobias Sergel.
-
E.
Eli Segal
Eli Segal was an American political strategist and nonprofit leader known for his senior roles in Democratic campaigns and for helping launch major national service initiatives like AmeriCorps.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc050a888190ac204d1e736200c5 |
completed | April 20, 2026, 10:12 a.m. |
Created at: April 10, 2026, 1:30 p.m.