Triple
T34216143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the man in the water |
E877793
|
entity |
| Predicate | numberOfPeopleHelpedRescue |
P205367
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [the man in the water, numberOfPeopleHelpedRescue, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPeopleHelpedRescue Context triple: [the man in the water, numberOfPeopleHelpedRescue, 5]
-
A.
numberOfRescuers
Indicates the quantity of rescuers involved in or assigned to a particular rescue-related situation or event.
-
B.
estimatedNumberOfPeopleSaved
Indicates the approximate count of individuals whose lives were preserved or harm was averted as a result of a particular action, intervention, or entity.
-
C.
rescuedDuring
Indicates that one entity was rescued in the course of, or as part of, a specified event or time period.
-
D.
usedMeansToRescue
Indicates that one entity employed a particular method, tool, or means in order to carry out a rescue.
-
E.
numberOfPeopleTrapped
Indicates the count of individuals who are currently trapped in a given situation or location.
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:55 a.m.