Triple
T30213084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Coubre memorial rally |
E768122
|
entity |
| Predicate | hasInjuredCountCommemorated |
P140653
|
FINISHED |
| Object | hundreds injured |
—
|
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: hundreds injured | Statement: [La Coubre memorial rally, hasInjuredCountCommemorated, hundreds injured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInjuredCountCommemorated Context triple: [La Coubre memorial rally, hasInjuredCountCommemorated, hundreds injured]
-
A.
memorializesInjured
Indicates that one entity serves as a memorial or tribute to another entity that has been injured.
-
B.
numberCommemoratedOnMemorial
chosen
Indicates the quantity of individuals or entities that are honored or remembered on a particular memorial.
-
C.
commemoratedIn
Indicates that something is honored, remembered, or recognized within a particular work, event, place, or medium.
-
D.
numberOfMissingCommemorated
Indicates the count of commemorated entities that are missing or unaccounted for in a given context.
-
E.
numberOfCommemoratedPersons
Indicates the count of distinct persons who are commemorated or honored in a given context or entity.
- 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_69f2247fd8b8819087fcf83cb7a05eb8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fecd0a732c819097bdd3eb69b6158c |
completed | May 9, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69fecc0318d481908b5b20598a76a9fe |
completed | May 9, 2026, 5:54 a.m. |
Created at: April 29, 2026, 7:33 p.m.