Triple
T33651230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NX |
E862103
|
entity |
| Predicate | associatedWithCountryOrRegion |
P206621
|
FINISHED |
| Object | Macau |
E7092
|
NE 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: Macau | Statement: [NX, associatedWithCountryOrRegion, Macau]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCountryOrRegion Context triple: [NX, associatedWithCountryOrRegion, Macau]
-
A.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
-
B.
correspondsToCountry
Indicates that one entity is associated with, matches, or represents a specific country.
-
C.
associatedCountryCode
Indicates that there is a relationship linking something to the country identified by the given country code.
-
D.
associatedCountryAtTheTime
Indicates the country with which an entity was linked or affiliated during a specific historical time or event, rather than its current or permanent country association.
-
E.
associatedCountryViaNotableBearer
Indicates a relationship where an entity is linked to a country through a notable person who bears or represents that entity (such as a name, title, or work).
- F. None of above. chosen
Provenance (5 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36271db1548190bb1ccf04d2e1a55c |
completed | June 20, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:42 a.m.