Triple
T17169185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow theater hostage crisis |
E416683
|
entity |
| Predicate | hostageFatalities |
P88183
|
FINISHED |
| Object | over 120 hostages killed |
—
|
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: over 120 hostages killed | Statement: [Moscow theater hostage crisis, hostageFatalities, over 120 hostages killed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostageFatalities Context triple: [Moscow theater hostage crisis, hostageFatalities, over 120 hostages killed]
-
A.
hostages
Indicates that one party is forcibly holding another party captive, typically to compel a third party to meet certain demands or conditions.
-
B.
numberOfHostagesKilled
chosen
Indicates the number of hostages who were killed in the context of a specific event or situation.
-
C.
numberOfHostages
Indicates the quantity of hostages involved in a particular situation, event, or context.
-
D.
notableVictim
Indicates that the subject is a person or entity who is notably recognized as a victim of the object (such as an event, crime, or harmful action).
-
E.
notableVictims
Indicates that the object is a person or group who is especially well-known or significant as a victim of the subject.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f9173ee48190bc46622c78479603 |
completed | April 18, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.