Triple
T3644237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sukkur Barrage |
E77258
|
entity |
| Predicate | hasSpanLength |
P4063
|
FINISHED |
| Object | 18.3 metres |
—
|
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: 18.3 metres | Statement: [Sukkur Barrage, hasSpanLength, 18.3 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpanLength Context triple: [Sukkur Barrage, hasSpanLength, 18.3 metres]
-
A.
hasMainSpanLength
chosen
Indicates the relationship specifying the primary or main span’s length associated with an entity.
-
B.
isSpanning
Indicates that one entity extends across, covers, or bridges the full width, extent, or duration of another entity.
-
C.
numberOfSpans
Indicates the total count of distinct spans or segments associated with an entity or within a specified context.
-
D.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
E.
isFeatureLength
Indicates that something (typically a film or video) has a duration long enough to be considered a full-length, standard feature.
- 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_69ad85de1b988190a45f8dbfebc806fc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc35c28908190b253f4835918a2b4 |
completed | March 8, 2026, 6:43 p.m. |
| PD | Predicate disambiguation | batch_69adb8445b2c8190ab07f6ad4e010d0e |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:24 p.m.