Triple
T2783041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastside of King County |
E61740
|
entity |
| Predicate | hasIndustryPresence |
P17483
|
FINISHED |
| Object | Microsoft (headquarters in Redmond) |
—
|
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: Microsoft (headquarters in Redmond) | Statement: [Eastside of King County, hasIndustryPresence, Microsoft (headquarters in Redmond)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustryPresence Context triple: [Eastside of King County, hasIndustryPresence, Microsoft (headquarters in Redmond)]
-
A.
hasCorporatePresence
chosen
Indicates that an organization maintains an official operational or business presence (such as offices, facilities, or legal registration) in a particular location or context.
-
B.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
C.
hasPrincipalIndustry
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
- 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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.