Triple
T23093941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hmar language |
E575831
|
entity |
| Predicate | hasRiskStatus |
P150896
|
FINISHED |
| Object | potentially vulnerable |
—
|
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: potentially vulnerable | Statement: [Hmar language, hasRiskStatus, potentially vulnerable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRiskStatus Context triple: [Hmar language, hasRiskStatus, potentially vulnerable]
-
A.
hasRiskFrom
Indicates that one entity is exposed to or may suffer potential harm, loss, or adverse effects as a result of another entity.
-
B.
hasRiskFactorFor
Indicates that one entity contributes to or increases the likelihood of another entity experiencing a particular risk or adverse outcome.
-
C.
hasRiskyStrategy
Indicates that an entity employs or is associated with a strategy characterized by a high level of risk or potential for significant loss.
-
D.
hasCountryOfRisk
Indicates that an entity is associated with a country where it faces significant exposure, vulnerability, or potential risk.
-
E.
hasWithdrawalRisk
Indicates that discontinuing or reducing something is associated with a risk of withdrawal effects or adverse reactions.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de2ed088190971ff08c58b15aad |
completed | April 29, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:57 p.m.