Triple
T244076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNICA |
E4997
|
entity |
| Predicate | hasMemberCharacteristic |
P274
|
FINISHED |
| Object | located in European capital cities |
—
|
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: located in European capital cities | Statement: [UNICA, hasMemberCharacteristic, located in European capital cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberCharacteristic Context triple: [UNICA, hasMemberCharacteristic, located in European capital cities]
-
A.
hasCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular attribute, feature, or quality.
-
B.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
C.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
-
D.
hasAdherent
Indicates that an entity is a follower, supporter, or member attached to another entity (such as a person, organization, belief, or movement).
-
E.
hasMemberState
Indicates that an entity includes or comprises another entity as one of its constituent member states within a larger organizational or political structure.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.