Triple
T392016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia 76ers |
E8900
|
entity |
| Predicate | cityDerby |
P10824
|
FINISHED |
| Object | none |
—
|
LITERAL 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: none | Statement: [Philadelphia 76ers, cityDerby, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityDerby Context triple: [Philadelphia 76ers, cityDerby, none]
-
A.
cityRivalry
Indicates a competitive or adversarial relationship that exists between two cities, often involving sports, economics, culture, or historical tensions.
-
B.
city1
Indicates that the subject is classified as a city.
-
C.
game3City
Indicates that a game or match (in a series or sequence) takes place in, or is associated with, a particular city.
-
D.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
E.
game2City
Indicates a relationship where a game is associated with, takes place in, or is otherwise linked to a particular city.
- F. None of above. chosen
Provenance (4 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec7492288190bf33c9c869a0710f |
completed | Feb. 28, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69a2e96a8ca48190abbd8de9b02c115c |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.