Triple
T11448162
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dibiasky comet |
E271316
|
entity |
| Predicate | fictionalTimeToImpact |
P99347
|
FINISHED |
| Object | approximately six months |
—
|
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: approximately six months | Statement: [Dibiasky comet, fictionalTimeToImpact, approximately six months]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalTimeToImpact Context triple: [Dibiasky comet, fictionalTimeToImpact, approximately six months]
-
A.
fictionalTime
Indicates that the associated time or temporal reference exists only within a fictional or imagined context, rather than in real-world chronology.
-
B.
timeHorizonOfImpact
Indicates the span of time over which an action, event, or factor is expected to produce its effects or consequences.
-
C.
impactTimeLocal
Indicates the specific local time at which an impact event occurs or is expected to occur.
-
D.
inceptionTime
Indicates the specific point in time when an entity, event, or relationship begins or is first established.
-
E.
timeOfDeath
Indicates the specific time at which an entity (typically a person or organism) died.
- F. None of above. chosen
Provenance (4 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d81c6d4890819082fb4a670feb2629 |
completed | April 9, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69d7e7162b288190a0bfb89f7eb747c7 |
completed | April 9, 2026, 5:51 p.m. |
| PDg | Predicate description generation | batch_69d800115af08190bba53dd3ff561ca1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:35 p.m.