Triple
T30578920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union of Medical Care and Relief Organizations |
E778326
|
entity |
| Predicate | focusesOnCrisis |
P134629
|
FINISHED |
| Object | Syrian civil war |
—
|
NE NERFINISHED |
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: Syrian civil war | Statement: [Union of Medical Care and Relief Organizations, focusesOnCrisis, Syrian civil war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnCrisis Context triple: [Union of Medical Care and Relief Organizations, focusesOnCrisis, Syrian civil war]
-
A.
viewOnCrises
Indicates a stance, opinion, or perspective that an entity holds regarding one or more crises.
-
B.
crisisManagement
chosen
Indicates the relationship in which an entity plans for, responds to, and mitigates the impact of disruptive or emergency situations.
-
C.
crisisRelatedTo
Indicates a relationship where one situation, event, or condition is connected to, associated with, or relevant to a crisis.
-
D.
crisisAddressed
Indicates that an entity has taken action to respond to, manage, or resolve a specific crisis.
-
E.
typeOfCrisis
Indicates the specific category or nature of a crisis that an entity is experiencing or associated with.
- 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_69f224a04b248190b0ca443ec86207b8 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7626667f48190ad90867eb67ec582 |
completed | May 3, 2026, 2:57 p.m. |
| PD | Predicate disambiguation | batch_69f76175d6608190b60b268e20f49ed9 |
completed | May 3, 2026, 2:53 p.m. |
Created at: April 29, 2026, 8:23 p.m.