Triple
T16852670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LG Twin Towers |
E409711
|
entity |
| Predicate | hasTwinBuildingRelation |
P96092
|
FINISHED |
| Object | each tower of the complex |
—
|
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: each tower of the complex | Statement: [LG Twin Towers, hasTwinBuildingRelation, each tower of the complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwinBuildingRelation Context triple: [LG Twin Towers, hasTwinBuildingRelation, each tower of the complex]
-
A.
hasArchitecturalTwin
Indicates that two entities share nearly identical architectural design, form, or structure, effectively making them architectural counterparts or duplicates.
-
B.
hasTwinStructureWith
chosen
Indicates that two entities share an identical or nearly identical structural form, typically as corresponding or mirrored counterparts.
-
C.
isTwinWith
Indicates that two entities are twins, sharing the same birth parents and being born at (or very near) the same time.
-
D.
hasTwinCityStructure
Indicates that one city has an officially recognized twin-city (sister-city) relationship structure with another city.
-
E.
hasTwinTown
Indicates that two towns or cities are officially paired in a twinning relationship, typically for cultural, social, or economic exchange.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37abadc81909d02d329403497d6 |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.