Triple
T5049128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaesong Industrial Region |
E113740
|
entity |
| Predicate | numberOfSouthKoreanFirmsAtPeak |
P17464
|
FINISHED |
| Object | over 120 |
—
|
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: over 120 | Statement: [Kaesong Industrial Region, numberOfSouthKoreanFirmsAtPeak, over 120]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSouthKoreanFirmsAtPeak Context triple: [Kaesong Industrial Region, numberOfSouthKoreanFirmsAtPeak, over 120]
-
A.
hasNumberOfCompanies
chosen
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
B.
teamCountAtPeak
Indicates the number of team members involved at the highest or peak point of activity, size, or performance.
-
C.
memberCountAtPeak
Indicates the highest number of members that an entity (such as a group or organization) has had at any point in time.
-
D.
KCGroup
Indicates that multiple entities are grouped together as members or elements of the same collection, category, or set.
-
E.
nationalCompanyOf
Indicates that a company operates as the primary or officially recognized national company of a specified country or nation.
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd715479f08190933604aebd34414f |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.