Triple
T27754327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palestine refugees |
E701297
|
entity |
| Predicate | mainHostCountries |
P115476
|
FINISHED |
| Object | Lebanon |
—
|
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: Lebanon | Statement: [Palestine refugees, mainHostCountries, Lebanon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainHostCountries Context triple: [Palestine refugees, mainHostCountries, Lebanon]
-
A.
mainHostCountry
chosen
Indicates the country that primarily serves as the host location for the associated entity or event.
-
B.
initialHostCountries
Indicates the countries that first hosted or received a given entity, event, or activity at its outset.
-
C.
eventHostCountries
Indicates that the subject countries serve as hosts for a particular event or set of events.
-
D.
notableHostCountries
Indicates that certain countries are recognized as prominent or significant locations for hosting a particular event, activity, or entity.
-
E.
lastHostCountry
Indicates the country that most recently hosted a particular event, activity, 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_69ef6a5193808190816eb7d0020b2d87 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f63894e5848190aec428392562ab06 |
completed | May 2, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 4:22 p.m.