Triple
T33729129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Five Little Pigs |
E864224
|
entity |
| Predicate | timeGapBetweenCrimeAndInvestigation |
P177252
|
FINISHED |
| Object | 16 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: 16 years | Statement: [Five Little Pigs, timeGapBetweenCrimeAndInvestigation, 16 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeGapBetweenCrimeAndInvestigation Context triple: [Five Little Pigs, timeGapBetweenCrimeAndInvestigation, 16 years]
-
A.
timeframeOfCrimes
Indicates the period or span of time during which the crimes occurred or were committed.
-
B.
timeBetweenAccidentAndThreats
Indicates the duration of time that passes between the occurrence of an accident and the subsequent emergence of related threats.
-
C.
hasCrimeInvestigation
Indicates that an entity is the subject of, or associated with, a formal investigation into a crime.
-
D.
frameForCrime
Indicates causing someone to be falsely perceived or officially treated as responsible for a crime they did not commit.
-
E.
inceptionTime
Indicates the specific point in time when an entity, event, or relationship begins or is first established.
- 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_69f3498a64cc8190b4b414c67b280d93 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb1c700c8190ad1286b4df5268c5 |
completed | May 3, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69f6f96dd4c8819093d6a7bd046a9ad5 |
completed | May 3, 2026, 7:29 a.m. |
| PDg | Predicate description generation | batch_69f6fa335b908190a20d92d5396203b5 |
completed | May 3, 2026, 7:33 a.m. |
Created at: May 1, 2026, 1:44 a.m.