Triple
T9307503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of St. Mary and the Martyrs |
E223923
|
entity |
| Predicate | oculusDiameter |
P87989
|
FINISHED |
| Object | about 8.9 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 8.9 metres | Statement: [Church of St. Mary and the Martyrs, oculusDiameter, about 8.9 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oculusDiameter Context triple: [Church of St. Mary and the Martyrs, oculusDiameter, about 8.9 metres]
-
A.
objectiveLensDiameter
Indicates the diameter of the objective lens used in an optical device, such as a camera or telescope.
-
B.
eyeType
Indicates the specific kind or category of eyes an entity has, such as their form, structure, or visual style.
-
C.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
-
D.
eyeCount
Indicates the number of eyes an entity has.
-
E.
canBeSeenWith
Indicates that two entities are observable together in the same context, setting, or time.
- 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd1daa21188190b1b2e508b0d09dcb |
completed | April 1, 2026, 1:29 p.m. |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:37 p.m.