Triple
T2604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambridge, Massachusetts |
E48
|
entity |
| Predicate | economy |
P71
|
FINISHED |
| Object | technology sector |
—
|
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: technology sector | Statement: [Cambridge, Massachusetts, economy, technology sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economy Context triple: [Cambridge, Massachusetts, economy, technology sector]
-
A.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
B.
economicSystem
Indicates the type or structure of the economic organization or system under which an entity operates or to which it belongs.
-
C.
capital
Indicates that one place serves as the official seat of government or primary administrative center for another political entity.
-
D.
currency
Indicates that one entity serves as the medium of exchange or monetary unit used by another entity (such as a country, region, or system).
-
E.
employer
Indicates a relationship where one entity hires, pays, and oversees the work of another entity.
- 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_69a22e0d37588190897cf37a323013f5 |
completed | Feb. 27, 2026, 11:51 p.m. |
| NER | Named-entity recognition | batch_69a23344daf8819083118bbac5f46568 |
completed | Feb. 28, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69a232e52e7c81909c072703e28e8c61 |
completed | Feb. 28, 2026, 12:12 a.m. |
Created at: Feb. 27, 2026, 11:55 p.m.