Triple
T35130321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine–Spanish relations |
E1014417
|
entity |
| Predicate | hasEmbassyOfPhilippinesIn |
P182313
|
FINISHED |
| Object | Madrid |
—
|
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: Madrid | Statement: [Philippine–Spanish relations, hasEmbassyOfPhilippinesIn, Madrid]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmbassyOfPhilippinesIn Context triple: [Philippine–Spanish relations, hasEmbassyOfPhilippinesIn, Madrid]
-
A.
haveEmbassyOfIndonesiaIn
Indicates that an entity hosts or contains an embassy representing Indonesia in a specified location.
-
B.
hasConsulateOfUnitedStatesIn
Indicates that a consulate of the United States is located in the specified place.
-
C.
hasDiplomaticStaffFrom
Indicates that an entity has diplomatic personnel who originate from or represent another specified entity.
-
D.
hasDiplomaticMission
Indicates that one entity maintains an official diplomatic representation, such as an embassy or mission, in the territory or jurisdiction of another entity.
-
E.
haveConsulatesOfIndonesiaIn
Indicates that consulates representing Indonesia are located within a specified place or jurisdiction.
- 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_69f76dd9c1848190af70d4882a2c1ad7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78ce78b508190955848e133398dc8 |
completed | May 3, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.