Triple
T23796941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Embassy in Beirut |
E588565
|
entity |
| Predicate | attackIncludedUSCitizensKilled |
P823
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [United States Embassy in Beirut, attackIncludedUSCitizensKilled, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackIncludedUSCitizensKilled Context triple: [United States Embassy in Beirut, attackIncludedUSCitizensKilled, true]
-
A.
casualtiesKilledUS
chosen
Indicates that the relationship specifies the number of U.S. individuals who were killed as casualties in an event or incident.
-
B.
governmentCasualties
Indicates that members of a government (such as officials, employees, or security forces) were killed, injured, or otherwise became casualties in an event or conflict.
-
C.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
-
D.
deathInTerroristAttack
Indicates that an entity died as a direct result of a terrorist attack.
-
E.
numberOfHostagesKilled
Indicates the number of hostages who were killed in the context of a specific event or situation.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c6ddc2d88190b6124d9fb2695d24 |
completed | April 29, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:50 p.m.