Triple
T1100607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASEAN Secretariat |
E24369
|
entity |
| Predicate | termLengthOfHead |
P540
|
FINISHED |
| Object | 5 years |
—
|
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: 5 years | Statement: [ASEAN Secretariat, termLengthOfHead, 5 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: termLengthOfHead Context triple: [ASEAN Secretariat, termLengthOfHead, 5 years]
-
A.
headTermLength
Indicates that a term (such as a word or phrase) has a specified length, typically measured in characters or tokens.
-
B.
termLength
chosen
Indicates the duration or period of time for which an agreement, position, or condition remains in effect.
-
C.
headProportion
Indicates the proportional relationship between the size of an entity’s head and a reference measure, such as its body or overall height.
-
D.
hasHeadCount
Indicates that an entity is associated with a specific number of individuals, typically representing the size or count of people (or similar units) related to it.
-
E.
stateHead
Indicates that one entity serves as the head or leader of a state-level governmental or administrative unit in relation to the other 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9c079f48190a0e0ddda182f7a01 |
completed | March 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69a4b745ef3481909a7ce4647c8567b3 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:43 p.m.