Triple
T7442220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulare Lake |
E171781
|
entity |
| Predicate | recurringPhenomenon |
P5108
|
FINISHED |
| Object | periodic reappearance during major flood 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: periodic reappearance during major flood years | Statement: [Tulare Lake, recurringPhenomenon, periodic reappearance during major flood years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recurringPhenomenon Context triple: [Tulare Lake, recurringPhenomenon, periodic reappearance during major flood years]
-
A.
phenomenon
Indicates that an entity is a perceptible event, occurrence, or process that can be observed or experienced.
-
B.
recurrence
chosen
Indicates that an event, condition, or state happens again or repeatedly over time, often after a period of absence or resolution.
-
C.
recurringDuring
Indicates that an event or state happens repeatedly within the time span or context defined by another event or interval.
-
D.
capturesPhenomenon
Indicates that one entity records, represents, or effectively reflects the occurrence or characteristics of a particular phenomenon.
-
E.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
- 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_69c68a65402881908f7869368eb746fb |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f36b9a3c81908abcc2a64d3e6061 |
completed | March 27, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.