Triple
T13304559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Mantell |
E316903
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mantel |
E480686
|
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: Mantel | Statement: [Joe Mantell, familyName, Mantel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mantel Context triple: [Joe Mantell, familyName, Mantel]
-
A.
Mantel
chosen
Mantel is a surname most prominently associated with the acclaimed British novelist Hilary Mantel, known for her historical fiction.
-
B.
Mantel
Mantel is a small municipality in the Upper Palatinate region of Bavaria, Germany.
-
C.
Tisch
Tisch is a surname most prominently associated with the American Tisch family, known for their influence in business, philanthropy, and the entertainment industry.
-
D.
Caroline Plate
The Caroline Plate is a small tectonic plate in the western Pacific Ocean, located north of New Guinea and interacting with several surrounding plates in a complex boundary zone.
-
E.
Banket
Banket is a small mining and farming town located in Zimbabwe's Mashonaland West Province.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d990a76adc8190ab9abcdb79a21ca8 |
completed | April 11, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716e161008190a48275ef54225d56 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:28 p.m.