Triple
T20659486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas State Highway 110 |
E507719
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
SH 110
SH 110 is a Texas state highway that runs through East Texas, connecting several rural communities and small cities.
|
E1442794
|
NE FINISHED |
How this triple was built (4 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: SH 110 | Statement: [Texas State Highway 110, abbreviation, SH 110]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SH 110 Context triple: [Texas State Highway 110, abbreviation, SH 110]
-
A.
SH 11
SH 11 is a Texas state highway that runs across the northeastern part of the state, connecting several rural communities and regional routes.
-
B.
SH 115
SH 115 is a state highway in Colorado that connects Colorado Springs to Cañon City, serving as a key route through the Front Range region.
-
C.
SH 10
SH 10 is a state highway in Colorado that runs east–west across the southern part of the state, connecting the cities of Walsenburg and La Junta.
-
D.
SH 114
SH 114 is a major Texas state highway running through the Dallas–Fort Worth area and connecting several key cities in North Texas.
-
E.
SH-1
SH-1 is the first-generation implementation of the SuperH 32-bit RISC microprocessor architecture developed for embedded systems.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SH 110 Triple: [Texas State Highway 110, abbreviation, SH 110]
Generated description
SH 110 is a Texas state highway that runs through East Texas, connecting several rural communities and small cities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SH 110 Target entity description: SH 110 is a Texas state highway that runs through East Texas, connecting several rural communities and small cities.
-
A.
SH 11
SH 11 is a Texas state highway that runs across the northeastern part of the state, connecting several rural communities and regional routes.
-
B.
SH 115
SH 115 is a state highway in Colorado that connects Colorado Springs to Cañon City, serving as a key route through the Front Range region.
-
C.
SH 10
SH 10 is a state highway in Colorado that runs east–west across the southern part of the state, connecting the cities of Walsenburg and La Junta.
-
D.
SH 114
SH 114 is a major Texas state highway running through the Dallas–Fort Worth area and connecting several key cities in North Texas.
-
E.
SH-1
SH-1 is the first-generation implementation of the SuperH 32-bit RISC microprocessor architecture developed for embedded systems.
- F. None of above. chosen
Provenance (5 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2eff7a88190be0bdea227616e02 |
completed | April 20, 2026, 11:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08c59bcd4c8190925addae1e67c5b4 |
completed | May 16, 2026, 7:29 p.m. |
| NEDg | Description generation | batch_6a08c6b50ea8819083ff85b85b2b6082 |
completed | May 16, 2026, 7:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08c7bf78b48190936455734ecf055d |
completed | May 16, 2026, 7:38 p.m. |
Created at: April 16, 2026, 11:43 a.m.