Triple
T6628518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triumphal Arch of the General Staff Building |
E149861
|
entity |
| Predicate | hasNumberOfPassages |
P44968
|
FINISHED |
| Object | one main central arch |
—
|
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: one main central arch | Statement: [Triumphal Arch of the General Staff Building, hasNumberOfPassages, one main central arch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfPassages Context triple: [Triumphal Arch of the General Staff Building, hasNumberOfPassages, one main central arch]
-
A.
numberOfPassages
chosen
Indicates the total count of distinct passages associated with or contained within a given entity or context.
-
B.
hasNumberOfParagraphs
Indicates that an entity is associated with a specific count of paragraphs it contains or comprises.
-
C.
hasCanonicalNumberOfArticles
Indicates that an entity is associated with a standard, officially recognized count of articles that define or describe it.
-
D.
hasTwoParagraphs
Indicates that the related content or text is composed of exactly two distinct paragraphs.
-
E.
numberOfChapters
Indicates the total count of chapters associated with a given 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.