Triple
T20679062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas area technology cluster |
E508240
|
entity |
| Predicate | hasIndustryFocus |
P70563
|
FINISHED |
| Object | telecommunications |
—
|
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: telecommunications | Statement: [Dallas area technology cluster, hasIndustryFocus, telecommunications]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustryFocus Context triple: [Dallas area technology cluster, hasIndustryFocus, telecommunications]
-
A.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
B.
hasIndustrySection
Indicates that an entity belongs to, is categorized under, or is associated with a particular industry section.
-
C.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
D.
hasIndustryRole
Indicates that an entity holds or performs a specific role, function, or position within a particular industry or sector.
-
E.
hasMarketFocus
chosen
Indicates that an entity concentrates its business activities, products, or services on a particular market or customer segment.
- 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_69e0b4c1164881909a3bf1e3ddb2bc32 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6bea516b88190b3e90d03fa981a44 |
completed | April 21, 2026, 12:02 a.m. |
| PD | Predicate disambiguation | batch_69e5c03caee881908be4dd25796a03d5 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:44 a.m.