Triple
T38587373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deeprun Tram |
E932374
|
entity |
| Predicate | supportsLowLevelCharacters |
P206551
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Deeprun Tram, supportsLowLevelCharacters, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLowLevelCharacters Context triple: [Deeprun Tram, supportsLowLevelCharacters, true]
-
A.
hasExtendedCharacterSet
Indicates that an entity supports or uses a character set that goes beyond a basic or standard set of characters.
-
B.
supportsUnicode
Indicates that an entity is capable of correctly handling, storing, or displaying Unicode-encoded text.
-
C.
containsCompatibilityCharacters
Indicates that one entity includes or is associated with characters that are designated as compatibility characters relative to another encoding or standard.
-
D.
supportsCharacterDifferences
Indicates that one entity accepts, encourages, or positively reinforces differences in traits, identities, or characteristics between characters.
-
E.
hasNumberOfBasicCharacters
Indicates the quantity of basic (non-accented or fundamental) characters associated with an entity.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c85e308819083dd67b96f457659 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:32 p.m.