Triple
T16531075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thames Group |
E401565
|
entity |
| Predicate | hasTypicalThickness |
P67473
|
FINISHED |
| Object | several tens to over 100 metres depending on location |
—
|
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: several tens to over 100 metres depending on location | Statement: [Thames Group, hasTypicalThickness, several tens to over 100 metres depending on location]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalThickness Context triple: [Thames Group, hasTypicalThickness, several tens to over 100 metres depending on location]
-
A.
hasMaximumThickness
Indicates that an entity possesses a specified upper limit on its thickness.
-
B.
typicalThicknessFormula
Indicates the standard or commonly used formula for calculating the thickness of something under typical conditions.
-
C.
thickness
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
D.
typicalDimension
chosen
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
E.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed741088190a285f8f9431810f3 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.