Triple
T34000334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tierkidi refugee camp |
E871797
|
entity |
| Predicate | protectionConcerns |
P179367
|
FINISHED |
| Object | gender-based violence |
—
|
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: gender-based violence | Statement: [Tierkidi refugee camp, protectionConcerns, gender-based violence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectionConcerns Context triple: [Tierkidi refugee camp, protectionConcerns, gender-based violence]
-
A.
concernsProvision
Indicates a relationship where something is about, deals with, or relates to the supplying or making available of resources, services, or necessities.
-
B.
protectionMeasures
Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
-
C.
concernsClause
Indicates that one entity (such as a document, statement, or discussion) is about, relates to, or addresses a particular clause.
-
D.
concernsFeature
Indicates that something is about, relates to, or involves a particular feature.
-
E.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
- 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f720cc1bfc8190a16118e3af8e9316 |
completed | May 3, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71fb0172c81908f23e95ff16b0dec |
completed | May 3, 2026, 10:13 a.m. |
Created at: May 1, 2026, 1:50 a.m.