Triple
T25913917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Soccer League |
E652973
|
entity |
| Predicate | hadMultipleIncarnations |
P76487
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [American Soccer League, hadMultipleIncarnations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMultipleIncarnations Context triple: [American Soccer League, hadMultipleIncarnations, true]
-
A.
hasMultipleIncarnations
chosen
Indicates that an entity exists or appears in more than one distinct form, version, or embodiment over time or context.
-
B.
hasRevivalsIn
Indicates that something has been brought back, renewed, or reintroduced in specific times, places, or contexts.
-
C.
hasIncarnationsOfGender
Indicates that an entity has different incarnations or forms that each express or are associated with a particular gender.
-
D.
secondIncarnationPortrayedBy
Indicates that the second incarnation of a character or entity is portrayed by a specific performer or actor.
-
E.
hasDoctorIncarnation
Indicates that an entity is associated with a specific incarnation or version of the Doctor (e.g., a particular regeneration or portrayal).
- 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_69e7ab3e025c819086771607157f0015 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f603e1f01c819082a9ea9385ce8433 |
completed | May 2, 2026, 2:02 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:30 a.m.