Triple
T31059417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tower of the Five Orders |
E791488
|
entity |
| Predicate | lowestOrder |
P170703
|
FINISHED |
| Object | Tuscan order |
—
|
NE NERFINISHED |
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: Tuscan order | Statement: [Tower of the Five Orders, lowestOrder, Tuscan order]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowestOrder Context triple: [Tower of the Five Orders, lowestOrder, Tuscan order]
-
A.
lowestRank
Indicates that the subject has the least or worst rank in an ordered set compared to all other related entities.
-
B.
lowestScore
Indicates that the associated value is the smallest (minimum) score among a set of scores.
-
C.
lowestCategory
Indicates that an entity belongs to the most specific or least general category within a classification hierarchy.
-
D.
lowerRankedOrder
Indicates that one entity holds a lower rank or priority in an ordered sequence relative to another entity.
-
E.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69575e1948190b242d53f918f172a |
completed | May 3, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
| PDg | Predicate description generation | batch_69f6938244648190a553b532387b812c |
completed | May 3, 2026, 12:14 a.m. |
Created at: April 29, 2026, 9 p.m.