Triple
T11575669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montauk Branch |
E274497
|
entity |
| Predicate | seasonalDemand |
P955
|
FINISHED |
| Object | summer travel to Hamptons |
—
|
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: summer travel to Hamptons | Statement: [Montauk Branch, seasonalDemand, summer travel to Hamptons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonalDemand Context triple: [Montauk Branch, seasonalDemand, summer travel to Hamptons]
-
A.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
primarySeasonality
Indicates the main or most characteristic time period or season during which something typically occurs or is most relevant.
-
C.
seasonMonths
Indicates the set of calendar months during which a given season occurs.
-
D.
hasSeasonalStructure
Indicates that something exhibits a recurring pattern, organization, or behavior that varies systematically with the seasons.
-
E.
seasonalReversal
Indicates a relationship where the usual seasonal pattern or effect between entities is inverted or occurs in the opposite manner from what is typically expected.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89049721081909278adfada668ef9 |
completed | April 10, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69d85dcbacd0819094d4a1237055affa |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.