Triple
T15055030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alton Lock and Dam |
E379465
|
entity |
| Predicate | auxiliaryLockWidth |
P60150
|
FINISHED |
| Object | 110 ft |
—
|
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: 110 ft | Statement: [Alton Lock and Dam, auxiliaryLockWidth, 110 ft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: auxiliaryLockWidth Context triple: [Alton Lock and Dam, auxiliaryLockWidth, 110 ft]
-
A.
lockedMeans
Indicates that one state, condition, or action guarantees or necessitates another, such that when the first is "locked in," the second must follow.
-
B.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
C.
entranceWidth
chosen
Indicates the measured horizontal span of an entrance opening that defines how wide the entry passage is.
-
D.
hasLockNumber
Indicates that an entity is associated with a specific lock identified by a number.
-
E.
maximumChannelWidth
Indicates the greatest allowable or observed width of a channel in the given context.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda92091c81909180f486edf01405 |
completed | April 15, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:01 a.m.