Triple
T12932537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altar of Zeus at Pergamon |
E309418
|
entity |
| Predicate | approximateFriezeLength |
P25800
|
FINISHED |
| Object | over 100 meters |
—
|
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: over 100 meters | Statement: [Altar of Zeus at Pergamon, approximateFriezeLength, over 100 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateFriezeLength Context triple: [Altar of Zeus at Pergamon, approximateFriezeLength, over 100 meters]
-
A.
numberOfFragmentsApprox
Indicates an approximate count of how many fragments or pieces are associated with the subject.
-
B.
approximateLengthInMeters
chosen
Indicates the estimated or roughly measured length of something expressed in meters.
-
C.
approximateBlockLength
Indicates that one entity specifies or estimates the length of a block in an approximate or non-exact manner.
-
D.
approximateSideLengthOrderOfMagnitude
Indicates that one entity’s side length is approximately the same order of magnitude as another entity’s side length, differing by no more than about a factor of ten.
-
E.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
- 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_69d7bdfa933c8190b5a27aa4a08a19b7 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97db69f548190a1a693bc0d6c191a |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 5:42 p.m.