Triple
T19539464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irving Gertz |
E488856
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gertz |
—
|
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: Gertz | Statement: [Irving Gertz, familyName, Gertz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gertz Context triple: [Irving Gertz, familyName, Gertz]
-
A.
Gertz
chosen
Gertz is a surname most notably associated with American actress and philanthropist Jami Gertz.
-
B.
Spiegel
Spiegel is a surname most prominently associated with Evan Spiegel, the co-founder and CEO of Snap Inc.
-
C.
Warta
Warta is a major river in western-central Poland that flows through several important cities before joining the Oder River.
-
D.
Warta
Warta is a small historic town in central Poland, situated in the Sieradz region along the Warta River.
-
E.
Biglow
Biglow is a surname and variant spelling of "Bigelow," borne by various individuals and families, particularly in English-speaking countries.
- 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63871d00881909ed7371ae5577957 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.