Triple
T33246630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Groningen gas extraction area |
E851118
|
entity |
| Predicate | HuizingeEarthquakeDate |
P12072
|
FINISHED |
| Object | 2012-08-16 |
—
|
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: 2012-08-16 | Statement: [Groningen gas extraction area, HuizingeEarthquakeDate, 2012-08-16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: HuizingeEarthquakeDate Context triple: [Groningen gas extraction area, HuizingeEarthquakeDate, 2012-08-16]
-
A.
notableEarthquake
Indicates that an earthquake event is significant or noteworthy due to its magnitude, impact, or historical importance.
-
B.
earthquakeDate
chosen
Indicates the specific calendar date on which an earthquake event occurred.
-
C.
populationImpact2010Earthquake
Indicates the effect or consequences that the 2010 earthquake had on a population, such as changes in size, distribution, or demographic characteristics.
-
D.
earthquakeType
Indicates the specific classification or category of an earthquake based on its characteristics or cause.
-
E.
deadliestEarthquakeUntil
Indicates that one earthquake was the most lethal (had caused the highest number of deaths) of all earthquakes up to a specified point 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_69f34962386c81909ddc3bf9e18ddeb8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:31 a.m.