Triple
T3438354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Scenic Area |
E72508
|
entity |
| Predicate | numberOfDesignations |
P48270
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [National Scenic Area, numberOfDesignations, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDesignations Context triple: [National Scenic Area, numberOfDesignations, 40]
-
A.
hasDesignation
Indicates that an entity holds or is assigned a specific title, label, or formal designation.
-
B.
numberOfIndicators
Indicates the total count of indicators associated with or relevant to a given entity or context.
-
C.
canBeDesignatedBy
Indicates that one entity is capable of being assigned, labeled, or identified by another entity as its designation.
-
D.
internationalDesignation
Indicates that an entity has been assigned a formal status, code, or recognition by an international body or under an internationally agreed system.
-
E.
divisionTitleCount
Indicates the number of titles or championships associated with a particular division.
- 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_69ad85af50288190a854b76653deee6f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9f575cc8190866929b1e8930143 |
completed | March 8, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69adae00ad588190bef24373b58a2e1a |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:16 p.m.