Triple
T1503116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MLS Next Pro |
E33839
|
entity |
| Predicate | hasAgeFocus |
P29430
|
FINISHED |
| Object | player development |
—
|
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: player development | Statement: [MLS Next Pro, hasAgeFocus, player development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeFocus Context triple: [MLS Next Pro, hasAgeFocus, player development]
-
A.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
B.
hasLowerAge
Indicates that one entity is younger in age than another entity.
-
C.
agePattern
Indicates a relationship where entities share or follow a specific configuration, distribution, or rule regarding their ages.
-
D.
focusesOnYears
Indicates that something is primarily concerned with or directed toward specific years or time periods.
-
E.
typicalEligibilityAge
Indicates the usual or standard age at which an entity qualifies for or becomes eligible for a particular status, benefit, or activity.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
| PDg | Predicate description generation | batch_69a90582f2548190bc0a6bdcd6d9d015 |
completed | March 5, 2026, 4:24 a.m. |
Created at: March 4, 2026, 7:24 p.m.