Triple
T12125259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Parisian Macao |
E288793
|
entity |
| Predicate | numberOfEiffelTowerReplicas |
P103527
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [The Parisian Macao, numberOfEiffelTowerReplicas, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEiffelTowerReplicas Context triple: [The Parisian Macao, numberOfEiffelTowerReplicas, 1]
-
A.
numberOfObservationDecks
Indicates the count of observation decks associated with or present in an entity.
-
B.
towerCount
Indicates the number of towers associated with or present in a given entity or context.
-
C.
numberOfSculptures
Indicates the quantity of sculptures associated with a given entity or context.
-
D.
numberOfTowers
Indicates the quantity of towers associated with or contained by a given entity.
-
E.
numberOfPavilions
Indicates the total count of pavilions associated with a given entity or context.
- 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_69d6ab4b5e4c81909950b17151eb0951 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91841615c819097f20a7447a1b8f4 |
completed | April 10, 2026, 3:33 p.m. |
| PD | Predicate disambiguation | batch_69d91508f8008190b3a90ec0bf0953ca |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d9183ec1008190b437b7d5e1f52830 |
completed | April 10, 2026, 3:33 p.m. |
Created at: April 8, 2026, 9:49 p.m.