Triple
T423947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Flyers |
E8163
|
entity |
| Predicate | mascotIntroduced |
P3757
|
FINISHED |
| Object | 2018 |
—
|
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: 2018 | Statement: [Philadelphia Flyers, mascotIntroduced, 2018]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mascotIntroduced Context triple: [Philadelphia Flyers, mascotIntroduced, 2018]
-
A.
debutedAsMascotFor
chosen
Indicates that an entity first appeared or was introduced in the role of a mascot representing another entity.
-
B.
hasMascot
Indicates that an entity is represented or symbolized by a particular mascot.
-
C.
introducedDuring
Indicates that one entity was first brought into existence, use, or awareness within the time period, event, or context specified by the other entity.
-
D.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
E.
introducedAsBrandBy
Indicates that one entity was presented or launched to the public or a market as a brand by another entity.
- F. None of above.
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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eed3e4cc8190ba6aff3bd1adb06f |
completed | Feb. 28, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.