Triple
T35385187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanauan, Leyte |
E1022770
|
entity |
| Predicate | typhoonHaiyanYear |
P61079
|
FINISHED |
| Object | 2013 |
—
|
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: 2013 | Statement: [Tanauan, Leyte, typhoonHaiyanYear, 2013]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typhoonHaiyanYear Context triple: [Tanauan, Leyte, typhoonHaiyanYear, 2013]
-
A.
typhoonImpactYear
chosen
Indicates the year in which a typhoon had its primary or recorded impact on a given entity or location.
-
B.
tsunamiDate
Indicates the date on which a tsunami event occurred or is recorded.
-
C.
notableTsunamiEvent
Indicates that a tsunami event is of particular significance or prominence, such as being historically important, unusually large, or widely recognized.
-
D.
hasTropicalCyclones
Indicates that the specified region or area experiences tropical cyclones as part of its typical weather or climate conditions.
-
E.
firstLandfallYear
Indicates the calendar year in which something (typically a storm or similar event) first makes landfall.
- 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f50080819095ff3c2cefc74fea |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.