Triple
T18445754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talbot Street, Dublin |
E450651
|
entity |
| Predicate | numberOfBombsOnStreetIn1974DublinBombings |
P131646
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Talbot Street, Dublin, numberOfBombsOnStreetIn1974DublinBombings, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBombsOnStreetIn1974DublinBombings Context triple: [Talbot Street, Dublin, numberOfBombsOnStreetIn1974DublinBombings, 1]
-
A.
timeOfFirstDublinExplosion
Indicates the specific time at which the first explosion occurred in Dublin.
-
B.
numberOfPeopleKilledInBombing
Indicates the total count of people who were killed as a direct result of a specific bombing event.
-
C.
dateOfAbbeyBombing
Indicates the specific calendar date on which the bombing of the abbey took place.
-
D.
numberOfSuicideBombers
Indicates the quantity of individuals who carry out or are intended to carry out suicide bombing attacks.
-
E.
cityBombed
Indicates that a particular city was subjected to a bombing attack.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c15127881909d23b6dd45d7ccc9 |
completed | April 19, 2026, 6:16 p.m. |
| PD | Predicate disambiguation | batch_69e469c943a4819094c8fdc5971ad3a7 |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:30 a.m.