Triple
T60650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isthmus of Panama |
E1204
|
entity |
| Predicate | hasLengthApproximately |
P266
|
FINISHED |
| Object | 640 kilometers |
—
|
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: 640 kilometers | Statement: [Isthmus of Panama, hasLengthApproximately, 640 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLengthApproximately Context triple: [Isthmus of Panama, hasLengthApproximately, 640 kilometers]
-
A.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
-
B.
isComparedTo
Indicates that one entity is evaluated or measured in relation to another to highlight similarities, differences, or relative qualities.
-
C.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
D.
hasStandardLetterCount
Indicates that an entity’s associated text or label contains a number of letters that matches a predefined standard or expected count.
-
E.
passengersCountApproximate
Indicates that the number of passengers involved is given as an approximate or estimated count rather than an exact figure.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251a1b8ac8190b44be4c3c41e5681 |
completed | Feb. 28, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69a24ea0bec48190b2af1fb287e9e692 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.