Triple
T13177683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Newgrange |
E313142
|
entity |
| Predicate | hasPassageLength |
P73716
|
FINISHED |
| Object | about 19 metres |
—
|
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: about 19 metres | Statement: [Newgrange, hasPassageLength, about 19 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassageLength Context triple: [Newgrange, hasPassageLength, about 19 metres]
-
A.
hasNumberOfParagraphs
Indicates that an entity is associated with a specific count of paragraphs it contains or comprises.
-
B.
hasEntrancePassageLength
chosen
Indicates the length of an entrance passage associated with an entity.
-
C.
hasParagraph
Indicates that one entity contains or is associated with a specific paragraph as part of its content or structure.
-
D.
hasSectionLength
Indicates that an entity is associated with a specific length value for one of its sections.
-
E.
articleLength
Indicates the length or size of an article, typically measured in units such as words, characters, or pages.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:14 p.m.