Triple
T38121157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Where the Dog Sits on the Tuckerbox |
E951938
|
entity |
| Predicate | hasLocationInText |
P134241
|
FINISHED |
| Object | Gundagai region |
—
|
NE NERFINISHED |
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: Gundagai region | Statement: [Where the Dog Sits on the Tuckerbox, hasLocationInText, Gundagai region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocationInText Context triple: [Where the Dog Sits on the Tuckerbox, hasLocationInText, Gundagai region]
-
A.
textLocation
Indicates the spatial or positional relationship of a piece of text within a larger document, page, or layout.
-
B.
hasTermLocation
Indicates that a term or concept is associated with, or occurs at, a specific location.
-
C.
hasLocationsIn
Indicates that an entity maintains a presence, operations, or facilities in one or more specified geographic locations.
-
D.
hasLocationComponent
Indicates that something includes, is associated with, or is composed of a specific location-related part or element.
-
E.
locatedInTextualSource
chosen
Indicates that information about an entity or relation appears within, or is documented by, a specific textual source.
- 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_69f76f07734c8190814e937e12257a78 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffc083a54c8190ac80d05ee8d20a6b |
completed | May 9, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69ffbfeb05b88190b4d50ce8124004d9 |
completed | May 9, 2026, 11:14 p.m. |
Created at: May 3, 2026, 4:21 p.m.