Triple
T2724083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loretto Chapel |
E60148
|
entity |
| Predicate | hasNumberOfTurns |
P30551
|
FINISHED |
| Object | 2 full 360-degree turns (staircase) |
—
|
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: 2 full 360-degree turns (staircase) | Statement: [Loretto Chapel, hasNumberOfTurns, 2 full 360-degree turns (staircase)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfTurns Context triple: [Loretto Chapel, hasNumberOfTurns, 2 full 360-degree turns (staircase)]
-
A.
numberOfTurns
chosen
Indicates the total count of discrete turns or rotations involved in an interaction, process, or motion.
-
B.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
C.
numberOfDraws
Indicates the total count of times an event, game, or contest has ended in a draw or tie.
-
D.
hasRound
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
-
E.
hasProperRounds
Indicates that an entity is associated with rounds that meet specified standards or criteria for being considered proper or valid.
- 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_69ab4b746d248190958e052045c09255 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdacc0a6881909b64a4d22e1d7690 |
completed | March 7, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69abd82586f88190a98f60d3247fe2d3 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.