Triple
T5333532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DMCC Metro Station |
E123367
|
entity |
| Predicate | hasModeConnection |
P62886
|
FINISHED |
| Object | bus |
—
|
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: bus | Statement: [DMCC Metro Station, hasModeConnection, bus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModeConnection Context triple: [DMCC Metro Station, hasModeConnection, bus]
-
A.
hasConnection
Indicates that there exists a link, association, or relationship between two entities.
-
B.
hasPortConnection
Indicates that one entity is linked to another via a port or interface through which data, power, or signals can be transmitted.
-
C.
hasWorkingMode
Indicates that an entity operates under or supports a particular mode or configuration of functioning.
-
D.
connectsWithMode
Indicates a relationship where one entity connects to another using a specified method, channel, or mode of connection.
-
E.
hasThemeConnection
Indicates a relationship where one entity is linked to another through a shared or related theme, topic, or conceptual focus.
- F. None of above. chosen
Provenance (4 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ac8e10819088b6a9e02d927044 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8501d53c81908371bd5195ba5703 |
completed | March 20, 2026, 5:33 p.m. |
Created at: March 20, 2026, 2 p.m.