Triple
T70722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1989 Loma Prieta earthquake |
E1415
|
entity |
| Predicate | timeUTC |
P1936
|
FINISHED |
| Object | 1989-10-18T00:04:15Z |
—
|
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: 1989-10-18T00:04:15Z | Statement: [1989 Loma Prieta earthquake, timeUTC, 1989-10-18T00:04:15Z]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeUTC Context triple: [1989 Loma Prieta earthquake, timeUTC, 1989-10-18T00:04:15Z]
-
A.
timeZoneHistorical
Indicates that there is a historical time zone relationship, specifying how an entity’s time zone (including offsets, rules, or changes) applied during past periods.
-
B.
UTCOffsetStandardTime
Indicates the time difference, in hours and minutes, that a location’s standard (non-daylight-saving) local time has from Coordinated Universal Time (UTC).
-
C.
UTCOffsetDaylightSavingTime
Indicates the time difference from Coordinated Universal Time (UTC) that applies to an entity specifically during daylight saving time periods.
-
D.
timeNotation
Indicates the specific system or format used to represent and write times (e.g., 12-hour vs 24-hour notation).
-
E.
time
chosen
Indicates a temporal relationship specifying when an event occurs or how entities are ordered or related in time.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.