Triple
T3220276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Round Tower |
E67494
|
entity |
| Predicate | hasSpiralRampWidth |
P46593
|
FINISHED |
| Object | wide enough for horse-drawn carriages |
—
|
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: wide enough for horse-drawn carriages | Statement: [Round Tower, hasSpiralRampWidth, wide enough for horse-drawn carriages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpiralRampWidth Context triple: [Round Tower, hasSpiralRampWidth, wide enough for horse-drawn carriages]
-
A.
hasSpiralPattern
Indicates that one entity exhibits or possesses a spiral-shaped pattern or arrangement in relation to another.
-
B.
hasIncline
Indicates that one entity possesses or exhibits a slope, tilt, or upward/downward angle relative to another reference.
-
C.
hasStairway
Indicates that one entity includes or is connected to another entity by a stairway providing vertical access between levels.
-
D.
hasHandrails
Indicates that an object, structure, or pathway is equipped with handrails for support or safety.
-
E.
hasTypicalColumnHeightToDiameterRatio
Indicates that there is a characteristic or commonly observed proportional relationship between a column’s height and its diameter.
- 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_69ad858b8adc8190ad989712c87a476b |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adae16f20081909d7f3bac016f961d |
completed | March 8, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69ad9e0bb6c48190a0659c67d40ee37c |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada148e9108190b363dd0f1a94ac8e |
completed | March 8, 2026, 4:18 p.m. |
Created at: March 8, 2026, 3:08 p.m.