Triple
T10646850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Witt |
E250857
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Witt |
E634752
|
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: Witt | Statement: [De Witt, hasPart, Witt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Witt Context triple: [De Witt, hasPart, Witt]
-
A.
Witt
chosen
Witt is a surname most prominently associated with American television and film producer Paul Junger Witt, known for creating and producing numerous popular TV series.
-
B.
WIT
WIT is the New York Stock Exchange ticker symbol for Wipro Limited, a major Indian multinational information technology services and consulting company.
-
C.
Wirth
Wirth is a Swiss surname most notably associated with computer scientist Niklaus Wirth, the designer of several influential programming languages.
-
D.
Wisser
The Wisser is a river in Germany that serves as a right-bank tributary of the Sieg.
-
E.
Wei
Wei was an ancient Chinese state during the Warring States period, known for its early strength and later decline before being annexed by the rising Qin dynasty.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe1cd6081909df9e4dc0fda1f0b |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a580d388190aea5edadd4afc0d1 |
completed | April 10, 2026, 10:31 p.m. |
Created at: April 8, 2026, 9:05 p.m.