Triple
T4952440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coyote Creek (Santa Clara County) |
E111198
|
entity |
| Predicate | hasFloodHistoryEvent |
P39409
|
FINISHED |
| Object | February 2017 San Jose flood |
—
|
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: February 2017 San Jose flood | Statement: [Coyote Creek (Santa Clara County), hasFloodHistoryEvent, February 2017 San Jose flood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodHistoryEvent Context triple: [Coyote Creek (Santa Clara County), hasFloodHistoryEvent, February 2017 San Jose flood]
-
A.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
-
B.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
C.
floodRecord
Indicates that an entity serves as a documented record or report of a flood event affecting another entity or area.
-
D.
notableFloodEvents
chosen
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
E.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71b6a5d481909ad6f5e0b752496c |
completed | March 20, 2026, 4:11 p.m. |
| PD | Predicate disambiguation | batch_69bd6c3aa1388190b3e0c8ee1ba1e4fa |
completed | March 20, 2026, 3:48 p.m. |
Created at: March 20, 2026, 1:31 p.m.