Triple
T10075601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gloria Katz |
E213748
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Katz |
E609090
|
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: Katz | Statement: [Gloria Katz, familyName, Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katz Context triple: [Gloria Katz, familyName, Katz]
-
A.
Katz
chosen
Katz is a common German and Ashkenazi Jewish surname, often associated with families of Central and Eastern European origin.
-
B.
Kato Kleines
Kato Kleines is a village located in the Florina regional unit of Western Macedonia in northern Greece.
-
C.
Catz
Catz is the surname of Safra Catz, a prominent business executive best known as the CEO of Oracle Corporation.
-
D.
Catz
Catz is a small commune in the Manche department of northwestern France, situated in the historic Normandy region.
-
E.
Catz
Catz is the informal nickname for St Catharine’s College, one of the constituent colleges of the University of Cambridge.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd0190d808190847ea0fa401ef06c |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29abcb72c81908c265f057532ccb7 |
completed | April 5, 2026, 5:24 p.m. |
Created at: March 30, 2026, 8:59 p.m.