Triple
T4465485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | .tv |
E98366
|
entity |
| Predicate | hasPopularityReason |
P55574
|
FINISHED |
| Object | semantic link to television |
—
|
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: semantic link to television | Statement: [.tv, hasPopularityReason, semantic link to television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPopularityReason Context triple: [.tv, hasPopularityReason, semantic link to television]
-
A.
hasPopularityInfluencedBy
Indicates that the popularity level of one entity is affected or shaped by another specified factor or entity.
-
B.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
C.
popularity
Indicates how widely liked, admired, or favored something or someone is by a group of people.
-
D.
popularityContext
Indicates the situational or domain-specific setting in which something’s popularity or level of public favor is evaluated.
-
E.
peakPopularity
Indicates the time or context in which something reaches its highest level of popularity relative to other times or contexts.
- F. None of above. chosen
Provenance (4 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_69b3454a7c608190944f5455c8031d73 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356991a588190be2f95fd957d7f99 |
completed | March 13, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69b34f65f6448190abfadb2ae5658798 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:34 p.m.