Triple
T10574176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mivtza Moshe |
E249567
|
entity |
| Predicate | estimatedNumberOfPeopleRescued |
P8803
|
FINISHED |
| Object | about 8000 |
—
|
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: about 8000 | Statement: [Mivtza Moshe, estimatedNumberOfPeopleRescued, about 8000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedNumberOfPeopleRescued Context triple: [Mivtza Moshe, estimatedNumberOfPeopleRescued, about 8000]
-
A.
estimatedNumberOfPeopleSaved
chosen
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
B.
numberOfRescuers
Indicates the quantity of rescuers involved in or assigned to a particular rescue-related situation or event.
-
C.
numberOfPeopleTrapped
Indicates the count of individuals who are currently trapped in a given situation or location.
-
D.
numberOfTroopsEvacuated
Indicates the quantity of troops that have been removed from a location or situation and transported to safety.
-
E.
usedMeansToRescue
Indicates that one entity employed a particular method, tool, or means in order to carry out a rescue.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52749dda08190b0c9627a931c5848 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:37 p.m.