Triple
T15640972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman numeral system |
E376061
|
entity |
| Predicate | exampleOfOverlineUsage |
P119570
|
FINISHED |
| Object | V̅ = 5000 |
—
|
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: V̅ = 5000 | Statement: [Roman numeral system, exampleOfOverlineUsage, V̅ = 5000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleOfOverlineUsage Context triple: [Roman numeral system, exampleOfOverlineUsage, V̅ = 5000]
-
A.
underlines
Indicates that one entity draws or applies a line beneath another entity, typically to emphasize or highlight it.
-
B.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
C.
overlies
Indicates that one entity is positioned directly above and covering or resting on another entity, often with partial or complete contact.
-
D.
overlays
Indicates that one entity is placed on top of or superimposed over another, partially or completely covering it in the same spatial area.
-
E.
lineUse
Indicates how a particular line (such as a route, track, or service line) is utilized or purposed within a system or network.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed06b388190bfebb77fe70e7df1 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.