Triple
T2836280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBT Media |
E62358
|
entity |
| Predicate | contentScope |
P14568
|
FINISHED |
| Object | global |
—
|
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: global | Statement: [IBT Media, contentScope, global]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contentScope Context triple: [IBT Media, contentScope, global]
-
A.
coverageScope
chosen
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
B.
scopeType
Indicates the specific range, level, or context within which a given relationship, rule, or action is defined or applies.
-
C.
GCContent
Indicates the proportion of guanine (G) and cytosine (C) bases relative to the total nucleotide content in a DNA or RNA sequence.
-
D.
textContent
Indicates that one entity is the textual content or written material contained within another entity.
-
E.
article2Content
Indicates that one article serves as the content or body text for another article or higher-level publication entity.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdeec60a08190b76b52042713d647 |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:01 p.m.