Triple
T16872499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leon County, Texas |
E421206
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Marquez, Texas
Marquez, Texas is a small rural city located in eastern Central Texas, known for its agricultural surroundings and close-knit community.
|
E525175
|
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: Marquez, Texas | Statement: [Leon County, Texas, contains, Marquez, Texas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marquez, Texas Context triple: [Leon County, Texas, contains, Marquez, Texas]
-
A.
Martindale, Texas
Martindale, Texas is a small rural city in Central Texas known for its historic charm and location along the San Marcos River.
-
B.
Mart, Texas
Mart, Texas is a small rural city in Central Texas known for its tight-knit community and agricultural surroundings.
-
C.
Murchison, Texas
Murchison, Texas is a small rural city located in eastern Texas within Henderson County.
-
D.
Quinlan, Texas
Quinlan, Texas is a small rural city in North Texas known for its proximity to Lake Tawakoni and its role as a local hub for the surrounding agricultural community.
-
E.
Velasco, Texas
Velasco, Texas was a historic Gulf Coast port town that played a key role in early Texas history, including as the site where treaties ending the Texas Revolution were signed.
- 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: Marquez, Texas Triple: [Leon County, Texas, contains, Marquez, Texas]
Generated description
Marquez, Texas is a small rural city located in eastern Central Texas, known for its agricultural surroundings and close-knit community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marquez, Texas Target entity description: Marquez, Texas is a small rural city located in eastern Central Texas, known for its agricultural surroundings and close-knit community.
-
A.
Martindale, Texas
Martindale, Texas is a small rural city in Central Texas known for its historic charm and location along the San Marcos River.
-
B.
Mart, Texas
chosen
Mart, Texas is a small rural city in Central Texas known for its tight-knit community and agricultural surroundings.
-
C.
Murchison, Texas
Murchison, Texas is a small rural city located in eastern Texas within Henderson County.
-
D.
Quinlan, Texas
Quinlan, Texas is a small rural city in North Texas known for its proximity to Lake Tawakoni and its role as a local hub for the surrounding agricultural community.
-
E.
Velasco, Texas
Velasco, Texas was a historic Gulf Coast port town that played a key role in early Texas history, including as the site where treaties ending the Texas Revolution were signed.
- F. None of above.
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_69d889d470fc8190b4aec199636c0c56 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3b7f31b448190a21e3e4d1a0d2f73 |
completed | April 18, 2026, 4:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08550c5ef481908d07d8e56ff91058 |
completed | May 16, 2026, 11:29 a.m. |
| NEDg | Description generation | batch_6a0855b26f0081909c2b74b888e0cd25 |
completed | May 16, 2026, 11:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08567e39548190bd201d744e5fa7e9 |
completed | May 16, 2026, 11:35 a.m. |
Created at: April 10, 2026, 5:29 a.m.