Triple
T1328249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A-League (1995–2004) |
E28379
|
entity |
| Predicate | relationToMLS |
P27261
|
FINISHED |
| Object | top competitor before MLS launch |
—
|
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: top competitor before MLS launch | Statement: [A-League (1995–2004), relationToMLS, top competitor before MLS launch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToMLS Context triple: [A-League (1995–2004), relationToMLS, top competitor before MLS launch]
-
A.
associatedHouse
Indicates a relationship where one entity is linked or connected to a particular house, typically as its related or corresponding house.
-
B.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
typeOfMunicipalRelationship
Indicates a formal type or category of administrative or cooperative relationship that exists between municipalities.
-
E.
relationToCreation
Indicates the nature of a connection or involvement an entity has with the origin, production, or bringing-into-existence of something.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c1d8188190b15a641a08345adc |
completed | March 1, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69a4beef6a188190996f8775bdda8f6c |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c0b1326081909aa6beec0cfe8d6c |
completed | March 1, 2026, 10:41 p.m. |
Created at: March 1, 2026, 7:55 p.m.