Triple
T27984851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maronite monasteries |
E706716
|
entity |
| Predicate | countryOfPresence |
P55443
|
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: [Maronite monasteries, countryOfPresence, Lebanon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfPresence Context triple: [Maronite monasteries, countryOfPresence, Lebanon]
-
A.
placeOfActivityPresentCountry
chosen
Indicates the country in which an entity is currently active or carries out its main activities.
-
B.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
C.
countryOfInteraction
Indicates that an interaction, event, or relationship took place within, or is associated with, a specific country.
-
D.
projectCountryAtTheTime
Indicates the country with which a project was associated at the specific time or period in question.
-
E.
positionInceptionCountry
Indicates the country in which a given position, role, or office was originally established or came into existence.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: April 27, 2026, 7:47 p.m.