Triple
T95165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Large Hadron Collider |
E1914
|
entity |
| Predicate | tunnelDepth |
P1176
|
FINISHED |
| Object | about 50 to 175 meters underground |
—
|
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 50 to 175 meters underground | Statement: [Large Hadron Collider, tunnelDepth, about 50 to 175 meters underground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunnelDepth Context triple: [Large Hadron Collider, tunnelDepth, about 50 to 175 meters underground]
-
A.
hasAverageDepth
chosen
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
B.
maximumDepth
Indicates the greatest extent or deepest level reached by something within a given context or structure.
-
C.
hasMaximumDepth
Indicates that an entity possesses a greatest or limiting depth value beyond which it does not extend.
-
D.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
E.
maximumTrunkDiameter
Indicates the largest thickness of a trunk measured across its widest point.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24ebb3da08190a8b82564f33cde3b |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.