Triple
T20627966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namanve |
E506869
|
entity |
| Predicate | sectorPresence |
P2193
|
FINISHED |
| Object | food processing industry |
—
|
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: food processing industry | Statement: [Namanve, sectorPresence, food processing industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sectorPresence Context triple: [Namanve, sectorPresence, food processing industry]
-
A.
districtPresence
Indicates that an entity operates in, is located within, or maintains an official presence in a particular district.
-
B.
sectorServed
chosen
Indicates the industry or economic sector that an entity primarily serves or targets with its activities, products, or services.
-
C.
sectorStrength
Indicates the relative performance or influence level of a specific sector compared to others within a broader system or market.
-
D.
hasCorporatePresence
Indicates that an organization maintains an official operational or business presence (such as offices, facilities, or legal registration) in a particular location or context.
-
E.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
- 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe645888190b639ebedc5b3041a |
completed | April 20, 2026, 10:42 p.m. |
| PD | Predicate disambiguation | batch_69e5a0155bd48190b3c769a12cc2c83d |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 16, 2026, 11:42 a.m.