Triple
T5707369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southeast Asian Games |
E125816
|
entity |
| Predicate | hasAgeCategories |
P19816
|
FINISHED |
| Object | senior |
—
|
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: senior | Statement: [Southeast Asian Games, hasAgeCategories, senior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeCategories Context triple: [Southeast Asian Games, hasAgeCategories, senior]
-
A.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
B.
eligibilityCategory
chosen
Indicates the classification or type of eligibility that applies to an entity within a given context.
-
C.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
-
D.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
E.
numberOfAges
Indicates the count of distinct ages associated with an entity or within a specified group or context.
- 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_69c0082d6fe48190b777fb383769e5c8 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024892fd88190a91133fc88365410 |
completed | March 22, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.