Triple
T22954132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salagdoong Beach |
E570105
|
entity |
| Predicate | hasApproximateBestMonths |
P100126
|
FINISHED |
| Object | November to May |
—
|
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: November to May | Statement: [Salagdoong Beach, hasApproximateBestMonths, November to May]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateBestMonths Context triple: [Salagdoong Beach, hasApproximateBestMonths, November to May]
-
A.
hasMonth
Indicates that something is associated with, occurs in, or is assigned to a specific month.
-
B.
hasAverageMonthLength
Indicates that an entity is associated with a specified average length of a month, typically expressed in days.
-
C.
hasMonthCount
Indicates a relationship where an entity is associated with a specific number of months.
-
D.
operatingMonthsApproximate
chosen
Indicates that the time period during which something operates is specified in approximate months rather than exact dates.
-
E.
hasApproximateRanking
Indicates that one entity is assigned a non-exact, estimated, or relative position or order with respect to others.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181ef7db4819093ab8117ed53c174 |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:46 p.m.