Triple
T24031113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Pozo del Tío Raimundo station |
E595106
|
entity |
| Predicate | numberOfFatalitiesInAttack |
P63692
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [El Pozo del Tío Raimundo station, numberOfFatalitiesInAttack, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFatalitiesInAttack Context triple: [El Pozo del Tío Raimundo station, numberOfFatalitiesInAttack, 21]
-
A.
numberOfVictimsKilled
chosen
Indicates the count of victims who were killed as a result of the referenced event or action.
-
B.
numberOfFatalitiesIn2011Attack
Indicates the count of people who were killed as a result of the 2011 attack.
-
C.
causedFatalities
Indicates that the referenced event or action directly resulted in one or more deaths.
-
D.
numberOfFatalitiesIn2018Attack
Indicates the number of people who were killed in the attack that occurred in 2018.
-
E.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d7709e5881908f5d4c0dd9f818c9 |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:55 p.m.