Triple
T29648560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamu |
E756071
|
entity |
| Predicate | hasBorderTradePost |
P80015
|
FINISHED |
| Object | Tamu border trade post |
—
|
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: Tamu border trade post | Statement: [Tamu, hasBorderTradePost, Tamu border trade post]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderTradePost Context triple: [Tamu, hasBorderTradePost, Tamu border trade post]
-
A.
hasBorderPostWith
Indicates that two regions or territories share a border where an official border post or checkpoint is located between them.
-
B.
borderTradePointWith
chosen
Indicates a location or facility where trade or commercial exchange occurs between two bordering regions or countries.
-
C.
connectsToBorderPost
Indicates that one entity is linked or leads directly to a border post, establishing a route or connection between them.
-
D.
hasCrossBorderTrade
Indicates that there is trade or commercial exchange occurring between entities located in different countries or jurisdictions.
-
E.
borderTradeType
Indicates the specific category or nature of trade that occurs across a border between two regions or countries.
- 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_69f0ef89d2c88190a6d0d5116ccd7cc9 |
completed | April 28, 2026, 5:34 p.m. |
| NER | Named-entity recognition | batch_69f9fd6834cc8190aa27153d6a99f3bb |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 28, 2026, 6:51 p.m.