Triple
T29517554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The University City of Cavite |
E748840
|
entity |
| Predicate | usedAsNicknameBy |
P37280
|
FINISHED |
| Object | local government of Dasmariñas |
—
|
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: local government of Dasmariñas | Statement: [The University City of Cavite, usedAsNicknameBy, local government of Dasmariñas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsNicknameBy Context triple: [The University City of Cavite, usedAsNicknameBy, local government of Dasmariñas]
-
A.
usedAsNicknameSince
Indicates that one entity has been used as a nickname for another entity starting from a specified point in time.
-
B.
usesNicknameIn
Indicates that one entity refers to another entity by a specific nickname within a particular context or setting.
-
C.
usesNicknameOf
Indicates that one entity refers to another entity by a nickname derived from or associated with that other entity’s name.
-
D.
usesNicknameFor
Indicates that one entity habitually refers to another entity by a nickname rather than their formal or given name.
-
E.
isOfficialNicknameOf
chosen
Indicates that one name is the formally recognized nickname or informal moniker used to refer to another 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_69f0bd461c208190bec20bbf24e02cc5 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: April 28, 2026, 4:38 p.m.